Unconventional hydrocarbon resources: geological statistics, petrophysical characterization, and field development strategies
Hydrocarbons exist in abundant quantity beneath the earth's surface. These hydrocarbons
are generally classified as conventional and unconventional hydrocarbons depending upon …
are generally classified as conventional and unconventional hydrocarbons depending upon …
A review on application of data-driven models in hydrocarbon production forecast
C Cao, P Jia, L Cheng, Q Jin, S Qi - Journal of Petroleum Science and …, 2022 - Elsevier
The accurate estimation of production is the bottleneck technique that constraints the
efficient development of oil and gas fields. However, such multivariate and asymmetric …
efficient development of oil and gas fields. However, such multivariate and asymmetric …
Well production forecasting based on ARIMA-LSTM model considering manual operations
Accurate and efficient prediction of well production is essential for extending a well's life
cycle and improving reservoir recovery. Traditional models require expensive computational …
cycle and improving reservoir recovery. Traditional models require expensive computational …
Time-series production forecasting method based on the integration of Bidirectional Gated Recurrent Unit (Bi-GRU) network and Sparrow Search Algorithm (SSA)
X Li, X Ma, F Xiao, C Xiao, F Wang, S Zhang - Journal of Petroleum Science …, 2022 - Elsevier
With the gowning demand of improving quality and benefit of unconventional resources,
time-series production prediction plays an increasingly essential role in economic …
time-series production prediction plays an increasingly essential role in economic …
Well performance prediction based on Long Short-Term Memory (LSTM) neural network
R Huang, C Wei, B Wang, J Yang, X Xu, S Wu… - Journal of Petroleum …, 2022 - Elsevier
Fast and accurate prediction of well performance continues to play an increasingly important
role in development adjustment and optimization. It is now possible to predict performance …
role in development adjustment and optimization. It is now possible to predict performance …
Attention-based LSTM network-assisted time series forecasting models for petroleum production
Petroleum production forecasting is the process of predicting fluid production from the wells
using historical data. In contrast to the traditional methods of analysing surface and …
using historical data. In contrast to the traditional methods of analysing surface and …
[HTML][HTML] Well production forecast in Volve field: Application of rigorous machine learning techniques and metaheuristic algorithm
CSW Ng, AJ Ghahfarokhi, MN Amar - Journal of Petroleum Science and …, 2022 - Elsevier
Developing a model that can accurately predict the hydrocarbon production by only
employing the conventional mathematical approaches can be very challenging. This is …
employing the conventional mathematical approaches can be very challenging. This is …
Estimated ultimate recovery prediction of fractured horizontal wells in tight oil reservoirs based on deep neural networks
S Luo, C Ding, H Cheng, B Zhang… - Advances in Geo …, 2022 - yandy-ager.com
Accurate estimated ultimate recovery prediction of fractured horizontal wells in tight
reservoirs is crucial to economic evaluation and oil field development plan formulation …
reservoirs is crucial to economic evaluation and oil field development plan formulation …
Machine learning based decline curve analysis for short-term oil production forecast
A Tadjer, A Hong, RB Bratvold - Energy Exploration & …, 2021 - journals.sagepub.com
Traditional decline curve analyses (DCAs), both deterministic and probabilistic, use specific
models to fit production data for production forecasting. Various decline curve models have …
models to fit production data for production forecasting. Various decline curve models have …
Machine learning for deepwater drilling: Gas-kick-alarm Classification using pilot-scale rig data with combined surface-riser-downhole monitoring
Gas kicks occur frequently in deepwater drilling because of the extremely narrow mud-
weight window [minimum 0.01 specific gravity (sg)]. The traditional kick-detection method …
weight window [minimum 0.01 specific gravity (sg)]. The traditional kick-detection method …